PT Freeport Indonesia’s mass-pull control strategy for rougher flotation

Supomo, A.; Yap, Erhan; Zheng, Xiaofeng; Banini, G.; Mosher, Janet; Partanen, A.G.

doi:10.1016/j.mineng.2008.07.002

Cited by 27 publications

(5 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The flowrate of solids to the concentrate (mass pull) has been used as an indicator of recovery at operating concentrators (Supomo et al 2008;Jameson 2010), on the basis that operating conditions that yield higher mass pull also yield higher mineral recovery. This is shown in Figure 7 for the same industrial experimental data as shown previously, where the two measures can be seen to be positively correlated.…”

Section: Indicative Flotation Performance: Proxies For Flotation Perfmentioning

confidence: 99%

The effect of particle size distribution on froth stability in flotation

Norori-McCormac

Brito-Parada

Hadler

et al. 2017

Separation and Purification Technology

View full text Add to dashboard Cite

Separation of particles of different surface properties using froth flotation is a widely-used industrial process, particularly in the minerals industry where it is used to concentrate minerals from ore. One of the key challenges in developing models to predict flotation performance is the interdependent nature of the process variables and operating parameters, which limits the application of optimising process control strategies at industrial scale. Froth stability, which can be quantified using air recovery (the fraction of air entering a flotation cell that overflows in the concentrate as unburst bubbles), has been shown to be linked to flotation separation performance, with stable froths yielding improved mineral recoveries. While it is widely acknowledged that there is an optimum particle size range for collection of particles in the pulp phase, the role of particle size on the measured air recovery and the resulting link to changes in flotation performance is less well understood. This is related to the difficulty in separating particle size and liberation effects.In this work, the effects of particle size distribution on air recovery are studied in a single species (silica) system using a continuous steady-state laboratory flotation cell. This allows an investigation into the effects of particle size distribution only on froth stability, using solids content and solids recovery as indicators of flotation performance. It is shown that, as the cell air rate is increased, the air recovery of the silica system passes through a peak, exhibiting the same froth behaviour as measured industrially. The air recovery profiles of systems with three different particle size distributions (d80 of 89.6, 103.5 and 157.1 m) are compared. The results show that, at lower air rates, the intermediate particle size distribution (103.5 m) yields the most stable froth, while at higher air rates, the finest particles (89.6 m) result in higher air recoveries. This is subsequently linked to changes in flotation performance. The results presented here highlight, for the first time, the link between particle size distribution in flotation feeds, air recovery and flotation performance. The results demonstrate that there is an optimal air rate for each particle size distribution, therefore changes in particle size distribution in the feed to flotation cells require a change in air rate in order to maximise mineral recovery.

show abstract

Section: Indicative Flotation Performance: Proxies For Flotation Perfmentioning

confidence: 99%

The effect of particle size distribution on froth stability in flotation

Norori-McCormac

Brito-Parada

Hadler

et al. 2017

Separation and Purification Technology

View full text Add to dashboard Cite

show abstract

“…This resulted in an estimated 1.3% increase in recovery. Supomo et al (2008), on the other hand, used a commercial image analysis system to control solids flowrate to concentrate down a bank of flotation cells using froth depth, demonstrating improved plant stability and recovery. In all of these systems, however, some 'tuning' of the controller is required in order to establish an acceptable range of the target.…”

mentioning

confidence: 99%

A flotation control system to optimise performance using peak air recovery

Shean

Hadler

Cilliers

2017

Chemical Engineering Research and Design

View full text Add to dashboard Cite

Automatic c ontrol of industrial flotation cells and circuits presents a set of significant challenges due to the number of variables, the sensitivity of flotation cells to variation in these variables and the complexity of predicting flotation performance and/ or deve loping a strategy for optim isation. Air recovery, a measure of froth stability, has been shown to pass through a peak as flotation cell aeration increases. Furthermore, the air rate at which the Peak Air Recovery (PAR) is obtained results in optimal flot ation performance, whether improved concentrate grade, recovery or both grade and recovery. Peak air recovery, therefore, presents a clear optimising control strategy for the operat ion of flotation cells which is generic to all flotation cells regardless of position in the flotation circuit. In this study, a novel control system based on PAR is developed and demonstrated using a large continuous laboratory flotation cell. In this study, a direct search optimisation algorithm based on the GSS (generating s et search) methodology was developed using a 70 l continuous flotation cell operating with a two - phase system (surfactant solution and air only). Characterisation of the laboratory system showed that it was stable for up to 6 hours and exhibited a reprodu cible peak in air recovery. A dynamic model of the response of the system with regards to changes in air recovery was developed that allowed simulations of the proposed optimising control system to be carried out. The optimisation algorithm was then applied to the experimental system. The tr ialled GSS algorithm was shown to find the PAR air rate when starting above, below and at the PAR air rate, and additionally with a disturbance introduced into the system. While the direct search approach can be slow, it is simple and robust. This demons trates an innovative approach to optimising control for froth flotation and is the first application of froth stability maximisation for flotation control

show abstract

“…This now requires a search for the froth velocity profile to achieve the target bank performance. An exponentially decreasing froth velocity profile is usually selected [18,19]. The form of the decay function appears to be based on mimicking how the banks are currently operated, which is not necessarily optimal, as the air profiling and PAR studies have shown.…”

Section: Discussionmentioning

confidence: 99%

“…Supomo et al [18] describe machine vision based control for a 9-cell rougher bank at the PT-Freeport copper/gold operation in Indonesia. The froth velocity profile is adjusted by manipulating froth depth designed to maximize concentrate rate (maximize recovery) subject to a trade-off between incremental recovery and additional transport and concentrate treatment charges.…”

Section: Mass-pull Profilingmentioning

confidence: 99%

An Overview of Optimizing Strategies for Flotation Banks

2012

View full text Add to dashboard Cite

Abstract:A flotation bank is a serial arrangement of cells. How to optimally operate a bank remains a challenge. This article reviews three reported strategies: air profiling, mass-pull (froth velocity) profiling and Peak Air Recovery (PAR) profiling. These are all ways of manipulating the recovery profile down a bank, which may be the property being exploited. Mathematical analysis has shown that a flat cell-by-cell recovery profile maximizes the separation of two floatable minerals for a given target bank recovery when the relative floatability is constant down the bank. Available bank survey data are analyzed with respect to recovery profiling. Possible variations on recovery profile to minimize entrainment are discussed.

show abstract

PT Freeport Indonesia’s mass-pull control strategy for rougher flotation

Cited by 27 publications

References 16 publications

The effect of particle size distribution on froth stability in flotation

The effect of particle size distribution on froth stability in flotation

A flotation control system to optimise performance using peak air recovery

An Overview of Optimizing Strategies for Flotation Banks

Contact Info

Product

Resources

About